Relative Binding Affinity Prediction of Charge-Changing Sequence Mutations with FEP in Protein–Protein Interfaces

Anthony J Clark,Christopher Negron,Kevin Hauser,Mengzhen Sun,Lingle Wang,Robert Abel,Richard A Friesner

doi:10.1016/j.jmb.2019.02.003

Anthony J Clark, Christopher Negron + Show 5 more

Open Access

https://doi.org/10.1016/j.jmb.2019.02.003

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Abstract

Building on the substantial progress that has been made in using free energy perturbation (FEP) methods to predict the relative binding affinities of small molecule ligands to proteins, we have previously shown that results of similar quality can be obtained in predicting the effect of mutations on the binding affinity of protein–protein complexes. However, these results were restricted to mutations which did not change the net charge of the side chains due to known difficulties with modeling perturbations involving a change in charge in FEP. Various methods have been proposed to address this problem. Here we apply the co-alchemical water approach to study the efficacy of FEP calculations of charge changing mutations at the protein–protein interface for the antibody–gp120 system investigated previously and three additional complexes. We achieve an overall root mean square error of 1.2 kcal/mol on a set of 106 cases involving a change in net charge selected by a simple suitability filter using side-chain predictions and solvent accessible surface area to be relevant to a biologic optimization project. Reasonable, although less precise, results are also obtained for the 44 more challenging mutations that involve buried residues, which may in some cases require substantial reorganization of the local protein structure, which can extend beyond the scope of a typical FEP simulation. We believe that the proposed prediction protocol will be of sufficient efficiency and accuracy to guide protein engineering projects for which optimization and/or maintenance of a high degree of binding affinity is a key objective.

Highlights

The prediction of the impact of residue mutations on protein–protein binding affinities is a major challenge for biomolecular simulation methodology
Building on the substantial progress that has been made in using free energy perturbation (FEP) methods to predict the relative binding affinities of small molecule ligands to proteins, we have previously shown that results of similar quality can be obtained in predicting the effect of mutations on the binding affinity of protein– protein complexes
These results were restricted to mutations which did not change the net charge of the side chains due to known difficulties with modeling perturbations involving a change in charge in FEP

Summary

Introduction

The prediction of the impact of residue mutations on protein–protein binding affinities is a major challenge for biomolecular simulation methodology. A number of approaches have been taken for prediction of relative protein–protein binding affinities. Tools such as FoldX use empirically trained energy functions based on experimentally measured protein and protein complex stability data [5]. Methods such as molecular mechanics generalized Born surface area (mm-GB/SA) and molecular mechanics (MM) Poisson–Boltzmann surface area use MM models with implicit (continuum) solvent molecular models to provide a more physics based approach at somewhat more computational cost [6].

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